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MODELING STREAM COMMUNICATIONS IN COMPONENT-BASED APPLICATIONS.

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Title: MODELING STREAM COMMUNICATIONS IN COMPONENT-BASED APPLICATIONS.
Authors: Danelutto, M.1, Laforenza, D.2, Tonellotto, N.2, Vanneschi, M.1, Zoccolo, C.1
Source: Scalable Computing: Practice & Experience. 2010, Vol. 11 Issue 3, p263-275. 13p. 2 Diagrams, 1 Chart, 2 Graphs.
Subjects: Grid computing, Component software, MODLER (Computer program language), Computer simulation, Service level agreements, Semantic networks (Information theory), Semantic computing
Abstract: Component technology is a promising approach to develop Grid applications, allowing to design very complex applications by hierarchical composition of basic components. Nevertheless, component applications on Grids have complex deployment models. Performance-sensitive decisions should be taken by automatic tools, matching developer knowledge about component performance with QoS requirements on the applications, in order to find deployment plans that satisfy a Service Level Agreement (SLA). This paper presents a steady-state performance model for component-based applications with stream communication semantics. The model strictly adheres to the hierarchical nature of component-based applications, and is of practical use in launch-time decisions. [ABSTRACT FROM AUTHOR]
Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: MODELING STREAM COMMUNICATIONS IN COMPONENT-BASED APPLICATIONS.
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  Data: <searchLink fieldCode="JN" term="%22Scalable+Computing%3A+Practice+%26+Experience%22">Scalable Computing: Practice & Experience</searchLink>. 2010, Vol. 11 Issue 3, p263-275. 13p. 2 Diagrams, 1 Chart, 2 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Grid+computing%22">Grid computing</searchLink><br /><searchLink fieldCode="DE" term="%22Component+software%22">Component software</searchLink><br /><searchLink fieldCode="DE" term="%22MODLER+%28Computer+program+language%29%22">MODLER (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Service+level+agreements%22">Service level agreements</searchLink><br /><searchLink fieldCode="DE" term="%22Semantic+networks+%28Information+theory%29%22">Semantic networks (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Semantic+computing%22">Semantic computing</searchLink>
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  Data: Component technology is a promising approach to develop Grid applications, allowing to design very complex applications by hierarchical composition of basic components. Nevertheless, component applications on Grids have complex deployment models. Performance-sensitive decisions should be taken by automatic tools, matching developer knowledge about component performance with QoS requirements on the applications, in order to find deployment plans that satisfy a Service Level Agreement (SLA). This paper presents a steady-state performance model for component-based applications with stream communication semantics. The model strictly adheres to the hierarchical nature of component-based applications, and is of practical use in launch-time decisions. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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